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    Probabilistic Open Set Recognition

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    http://hdl.handle.net/10976/306
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    Abstract
    Real-world tasks in computer vision, pattern recognition and machine learning often touch upon the open set recognition problem: multi-class recognition with incomplete knowledge of the world and many unknown inputs. An obvious way to approach such problems is to develop a recognition system that thresholds probabilities to reject unknown classes. Traditional rejection techniques are not about the unknown; they are about the uncertain boundary and rejection around that boundary. Thus traditional techniques only represent the “known unknowns”. However, a proper open set recognition algorithm is ...
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    Author(s)
    Jain, Lalit Prithviraj

    Advisor(s)
    Boult, Terrance E.

    Rights Access
    Embargo Expires: 12/09/2015

    Date Submitted
    2015
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